Sensing accuracy gain, unified performance analysis and optimization in 6G cooperative ISAC systems^✩,✩✩

Abstract

Sixth Generation (6G) mobile communication networks will involve sensing as a new function, with the overwhelming trend of Integrated Sensing And Communications (ISAC). Although expanding the serving range of the networks, there exists performance trade-off between communication and sensing, in that they have competitions on the physical resources. Different resource allocation schemes will result in different sensing and communication performance, thus influencing the system’s overall performance. Therefore, how to model the system’s overall performance, and how to optimize it are key issues for ISAC. Relying on the large-scale deployment of the networks, cooperative ISAC has the advantages of wider coverage, more robust performance and good compatibility of multiple monostatic and multistatic sensing, compared to the non-cooperative ISAC. How to capture the performance gain of cooperation is a key issue for cooperative ISAC. To address the aforementioned vital problems, in this paper, we analyze the sensing accuracy gain, propose a unified ISAC performance evaluation framework and design several optimization methods in cooperative ISAC systems. The cooperative sensing accuracy gain is theoretically analyzed via Cramér Rao lower bound. The unified ISAC performance evaluation model is established by converting the communication mutual information to the effective minimum mean squared error. To optimize the unified ISAC performance, we design the optimization algorithms considering three factors: base stations’ working modes, power allocation schemes and waveform design. Through simulations, we show the performance gain of the cooperative ISAC system and the effectiveness of the proposed optimization methods.

Keywords

6G / Integrated sensing and communications / Cooperative sensing / Cramér Rao lower bound / Orthogonal frequency division multiplexing

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